Product design question

Cancellation rate on Uber is currently at 25%. What would you do to bring this down to 5%?

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What this question tests

Root cause diagnosis and prioritization under a specific numeric target: can you break down cancellation causes and propose fixes that plausibly reach 5 percent.

How to approach it

  1. Segment cancellations by who cancels and when, rider before pickup, rider after driver assigned, or driver cancelling on rider.
  2. Hypothesize causes: long wait times, surge pricing sticker shock, driver no shows, and riders price comparing across apps while waiting.
  3. Prioritize by volume, assume driver cancellations and long ETA related rider cancellations are the largest share.
  4. Propose fixes matched to each cause: better driver matching to cut ETA, cancellation penalties for repeat driver cancellations, and price lock once a ride is confirmed.
  5. Sequence the rollout, fixing the largest driver side cause first since it compounds into rider side cancellations.
  6. Define success as cancellation rate trending from 25 percent toward 5 percent over a stated period, with weekly tracking.

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